Research questions:

Section 1 - Table 1 - [ ] For each LGA , which police region recorded maximum incidents? - [ ] How did the trend of incidents recorded in those police regions varied across the years.

Section 2

Section 3

#W What are the top 10 Suburbs wth maximum no of incidents so far?

Table 1: Suburbs with maximum incidents over the years
Suburb Total_Incidents
Melbourne 153694
Dandenong 58610
Frankston 57645
Preston 40185
Shepparton 39651
Mildura 39120
St Kilda 34484
Reservoir 32532
Werribee 32009
Richmond 31638

The table 1 clearly states that:

0.1 What are the top 10 Suburb’s recorded with most number of incidents in each Year ?

data3 %>% 
  group_by(Year,Suburb) %>%
  summarise(Total_Incidents = sum(Incidents_Recorded)) %>% 
  arrange(Year,desc(Total_Incidents)) %>% 
  slice_max(Total_Incidents,n = 10) %>% 
  mutate(Suburb1 = reorder_within(Suburb,Total_Incidents,Year)) %>% 
  ggplot(aes(x=Total_Incidents ,
             y=Suburb1,
             fill = Suburb)) +
  geom_col() +
  geom_text(aes(label = Total_Incidents)) +
  scale_y_reordered() +
  ylab("Suburb") +
  xlab("No. of Incidents") +
  ggtitle("Top 10 Suburb with most incidents recorded in each Years") +
  facet_wrap(~Year,ncol = 1, scales = "free")
Top 10 Suburb with most incidents recorded

Figure 1: Top 10 Suburb with most incidents recorded

The Figure 1 depicts that:

0.2 What were the top 10 Offence’s in each year ?

Top 10 Offences recorded

Figure 2: Top 10 Offences recorded

The Figure 2 showcases that:

0.3 What are the top 2 Offences for the most affected Suburb’s found in figure 1?

Figure 3: Top 10 Offfences Suburrb wise

The Figure 3 is clearly in coordination with figure 2 as we can see that Theft is most occurred crime across the affected Suburbs too

0.4 What is the trend of top 2 offences in each year w.r.t most affected Suburb?

The Figure ?? depicts that: